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MIT Creates Chip to Model Synapses
MrSeb writes with this excerpt from an Extreme Tech article: "With 400 transistors and standard CMOS manufacturing techniques, a group of MIT researchers have created the first computer chip that mimics the analog, ion-based communication in a synapse between two neurons. Scientists and engineers have tried to fashion brain-like neural networks before, but transistor-transistor logic is fundamentally digital — and the brain is completely analog. Neurons do not suddenly flip from '0' to '1' — they can occupy an almost-infinite scale of analog, in-between values. You can approximate the analog function of synapses by using fuzzy logic (and by ladling on more processors), but that approach only goes so far. MIT's chip is dedicated to modeling every biological caveat in a single synapse. 'We now have a way to capture each and every ionic process that's going on in a neuron,' says Chi-Sang Poon, an MIT researcher who worked on the project. The next step? Scaling up the number of synapses and building specific parts of the brain, such as our visual processing or motor control systems. The long-term goal would be to provide bionic components that augment or replace parts of the human physiology, perhaps in blind or crippled people — and, of course, artificial intelligence. With current state-of-the-art technology it takes hours or days to simulate a simple brain circuit. With MIT's brain chip, the simulation is faster than the biological system itself."
Due to their incompatibility with newer systems, meat bags are now obsolete.
FRA: STFU GTFO
I think the REAL problem is that even the smallest brains have several billion neurons, with each having 10's of thousands of connections to other neurons. This chip simulates ONE such connection.
That's a PCB-routing problem that you REALLY don't want, and way outside the scale of anything that we build (it's like every computer on the planet having 10,000 direct Ethernet connections to nearby computers - no switches, hubs, routers, etc. in order to simulate something approaching a small mouse's brain - not only a cabling and routing nightmare but where the hell do you plug it all in?). Not only that, by a real brain learns by breaking and creating connections all the time.
The analog nature of the neuron isn't really the key to making "artificial brains" - the problem is simply scale. We will never be able to produce enough of these chips and tie them together well enough to produce anything conventionally interesting (and certainly nothing that we could actually analyse any better than the brain of any other species). If we did, it would be unmanageably unprogrammable and unpredictable. If it did anything interesting on its own, we'd never understand how or why it did that.
And I think the claim that they know EVERYTHING about how a neuron works (at least one part of it) is optimistic at best.
I agree with everything about this statement except the word "never."
Never is a pretty bold word. It puts you in a pretty gutsy mindset; one that isn't entirely productive to rational scientific analysis. The word "never" is pretty commonly seen in the company of "famous last words."
I think you have to credit MIT researchers for knowing better where the cutting edge is than you, and the writers of the article for including the 1960s in this paragraph:
'Previously, researchers had built circuits that could simulate the firing of an action potential, but not all of the circumstances that produce the potentials. “If you really want to mimic brain function realistically, you have to do more than just spiking. You have to capture the intracellular processes that are ion channel-based,” Poon says.'
More than just spiking; from my AI lectures years ago I recall that the McCulloch-Pitts neuron model of the was a spiking model (excitatory inputs, inhibitory inputs, thresholds) etc.
Would the artificial brain have rights? If you wiped its artificial neurons, would it be murder? If you give it control of a physical robot arm and it hurt someone, how and to what extent could you "punish" it? The ethical questions are virtually endless when you start to play "god". I would think that would be obvious.
-- Let us endeavor so to live that when we pass even the undertaker shall be sorry. -- M. Twain
A single neuron-neuron connection has very low bandwidth, in effect transferring a single number (activation level) a few hundred times a second. Even if timing is important, you can simply accompany the level with a timestamp. A single 100 Mbs Ethernet connection is easily able to handle all those 10 000 connections.
Also, most of those 10 000 connections are to nearby neurons, presumably because long-distance communication involves the same latency and energy penalties in the brains as it does anywhere else. There are efficient methods to auto-cluster a P2P network so as to minimize total length of connections, for example Freenet does this; so, you could, in theory, run a distributed neural simulator even on standard Internet technology. In fact, I suspect that it could be possible to achieve human-level or higher artificial intelligence with existant computer power in this method right now.
So, who wants to start HAL@Home ?-)
Forget magic. Any technology distinguishable from divine power is insufficiently advanced.
You'll wipe your baby way more often than you'd want to.
Mod parent up. The linked article (and the MIT press release) are misleading. The closest thing I can find to a peer-reviewed publication by Poon has an abstract is here (no, I can't find anything throught the official EMBC channels--what a disgustingly closed conference):
https://embs.papercept.net/conferences/scripts/abstract.pl?ConfID=14&Number=2328
And there's some background on Poon's goals here:
http://www.frontiersin.org/Journal/FullText.aspx?ART_DOI=10.3389/fnins.2011.00108&name=neuromorphic_engineering
The goals seem to me to be about studying specific theories about information propagation across synapses as well as studying brain-computer interfaces. They never mention building a model of the entire visual system or any serious artificial intelligence. We have only the vaguest theories about how the visual system works beyond V1, and essentially no idea what properties of the synapse are important to make it happen.
About two years ago, while I was still doing my undergraduate research in neural modeling, I recall that the particular theory they're talking about--spike-timing dependent plasticity--was quite controversial. It might have been simply an artifact of the way the NMDA receptor worked. Nobody seemed to have any cohesive theory for why it would lead to intelligence or learning, other than vague references to the well-established Hebb rule.
Nor is it anything new. Remember this story from ages ago? Remember how well that returned on its promises of creating a real brain? That was spike-timing dependent plasticity as well, and unsurprisingly it never did anything resembling thought.
Slashdot, can we please stop posting stories about people trying to make brains on chips and post stories about real AI research?